Combined Use of Multi-Temporal Landsat-8 and Sentinel-2 Images for Wheat Yield Estimates at the Intra-Plot Spatial Scale

Bibliographic Details
Title: Combined Use of Multi-Temporal Landsat-8 and Sentinel-2 Images for Wheat Yield Estimates at the Intra-Plot Spatial Scale
Authors: Remy Fieuzal, Vincent Bustillo, David Collado, Gerard Dedieu
Source: Agronomy, Vol 10, Iss 3, p 327 (2020)
Publisher Information: MDPI AG, 2020.
Publication Year: 2020
Collection: LCC:Agriculture
Subject Terms: wheat, yield, in-season estimates, landsat-8, sentinel-2, random forest, Agriculture
More Details: The objective of this study is to address the capabilities of multi-temporal optical images to estimate the fine-scale yield variability of wheat, over a study site located in southwestern France. The methodology is based on the Landsat-8 and Sentinel-2 satellite images acquired after the sowing and before the harvest of the crop throughout four successive agricultural seasons, the reflectance constituting the input variables of a statistical algorithm (random forest). The best performances are obtained when the Normalized Difference Vegetation Index (NDVI) is combined with the yield maps collected during the crop rotation, the agricultural season 2014 showing the lower level of performances with a coefficient of determination (R2) of 0.44 and a root mean square error (RMSE) of 8.13 quintals by hectare (q.h−1) (corresponding to a relative error of 12.9%), the three other years being associated with values of R2 close or upper to 0.60 and RMSE lower than 7 q.h−1 (corresponding to a relative error inferior to 11.3%). Moreover, the proposed approach allows estimating the crop yield throughout the agricultural season, by using the successive images acquired from the sowing to the harvest. In such cases, early and accurate yield estimates are obtained three months before the end of the crop cycle. At this phenological stage, only a slight decrease in performance is observed compared to the statistic obtained just before the harvest.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2073-4395
Relation: https://www.mdpi.com/2073-4395/10/3/327; https://doaj.org/toc/2073-4395
DOI: 10.3390/agronomy10030327
Access URL: https://doaj.org/article/e666e6f4d5ec44aba1fbecbe5e5df830
Accession Number: edsdoj.666e6f4d5ec44aba1fbecbe5e5df830
Database: Directory of Open Access Journals
More Details
ISSN:20734395
DOI:10.3390/agronomy10030327
Published in:Agronomy
Language:English